The health of plants plays a crucial role in ensuring agricultural productivity and food security. Early detection of plant diseases can significantly reduce crop losses, leading to improved yields. This paper presents a novel approach for plant disease recognition using deep learning techniques. The proposed system automates the process of disease detection by analyzing leaf images, which are widely recognized as reliable indicators of plant health. By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high (...) accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. A. (shrink)

he health of plants plays a crucial role in ensuring agricultural productivity and food security. Early detection of plant diseases can significantly reduce crop losses, leading to improved yields. This paper presents a novel approach for plant disease recognition using deep learning techniques. The proposed system automates the process of disease detection by analyzing leaf images, which are widely recognized as reliable indicators of plant health. By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high (...) accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource (...) use. Additionally, it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (shrink)

Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource (...) use. Additionally, it discusses challenges like data privacy, barriers to technology adoption, and the ethical implications of AI in farming. Integrating AI into agricultural practices holds the promise of greater efficiency and sustainability, paving the way for future innovations. (shrink)

By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. Additionally, the (...) system is designed to provide real-time feedback to farmers, helping them take immediate corrective action. This automated approach eliminates the need for expert human intervention and can be deployed on mobile devices for ease of use in rural areas. The potential future applications of this system include integration with precision agriculture techniques and expansion to a wider range of crops. (shrink)

Abstract: The intelligent embedded agricultural robotic system is a low cost and efficient microcontroller robot which include; A soil moisture monitoring system which monitors the moisture content of the soil in the various parts of the field and the measured data to a microcontroller unit which in turn displays the received data on a Liquid Crystal Display to determine when to irrigate or spray the farm field. An automatic car, which follows a path designed in the field, i.e., a (...) white line on a black surface integrated with a spraying and irrigating mechanism for carrying out agricultural spray and irrigation. An automatic solar tracking system that tracks the sun’s position for maximum light intensity was used to charge the DC 12V battery which was used to power to the robotic system. A refilling system with obstacle detection feature was used for refilling water, chemical or fertilizer spray in the spraying and irrigating tank integrated with the line follower robotic system. This embedded system is useful for farmers who wish to monitor the soil moisture content of the field, and automate spraying and irrigation purposes at low costs and higher efficiency. (shrink)

The integration of Internet Protocol and Embedded Systems can enhance the communication platform. This paper describes the emerging smart technologies based on Internet of Things (IOT) and internet protocols along with embedded systems for monitoring and controlling smart devices with the help of WiFi technology and web applications. The internet protocol (IP) address has been assigned to the things to control and operate the devices via remote network that facilitates the interoperability and end-to-end communication among various devices c,onnected over a (...) network. The HTTP POST and HTTP GET command that supports the RESTful service have been used to ensure the transmission and reception of packets between the IOT Gateway and Cloud Database. The emerging smart technologies based on the Internet of Things (IoT) facilitated features like automation, controllability, interconnectivity, reliability which in turn turn paved the way for a wide range of acceptance amongst the masses. The Internet of Things (IoT) has brought in many new emerging technologies into varoius field like our daily lives, industry, agricultural sector, and many more. The world is experiencing the explosive growth with the advent of Internet of Things (IoT) these years. The potential growth of IoT is enoromous which is evidenced by all the human beings in our day to day life. (shrink)

The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. Additionally, the system is designed to provide real-time feedback to farmers, helping them take immediate corrective action. This automated approach eliminates the need for expert human intervention and can be deployed on mobile devices (...) for ease of use in rural areas. The potential future applications of this system include integration with precision agriculture techniques and expansion to a wider range of crops. (shrink)

The health of plants plays a crucial role in ensuring agricultural productivity and food security. Early detection of plant diseases can significantly reduce crop losses, leading to improved yields. This paper presents a novel approach for plant disease recognition using deep learning techniques. The proposed system automates the process of disease detection by analyzing leaf images, which are widely recognized as reliable indicators of plant health. By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high (...) accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. (shrink)

Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 images (...) belong to 3 species at a few developing phases. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results: found that CNN-driven lemon classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.48% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

Many economists have argued convincingly that automated systems employing present-day artificial intelligence have already caused massive technological displacement, which has led to stagnant real wages, fewer middle- income jobs, and increased economic inequality in developed countries like Canada and the United States. To address this problem various individuals have proposed measures to increase workers’ living standards, including the adoption of a universal basic income, increased public investment in education, increased minimum wages, increased worker control of firms, and investment in a (...) Green New Deal that will provide substantial employment in transitioning to green energy, buildings, and agriculture. In this paper I argue that both left-wing and right-wing positions in political philosophy, such as John Rawls’s Justice as Fairness and Robert Nozick’s Entitlement Theory, are committed to the conclusion that we should take political action to counteract the effects of technological displacement by undertaking such measures to increase workers’ living standards. (shrink)

Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit (...) people’s ability to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem. (shrink)

Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means of automated (...) theorem provers and finite model builders. The fundamental theorem of Leibniz’s theory is derived using these tools. (shrink)

Autonomous agricultural equipment represents a transformative innovation, combining cutting-edge technologies such as artificial intelligence (AI), robotics, and the Internet of Things (IoT). These machines address challenges such as labor shortages, environmental sustainability, and rising food demand. This paper explores the concept, key technologies, applications, and benefits of autonomous farming equipment. A comprehensive literature review highlights current advancements and challenges in the field. An experimental study evaluates the efficiency and impact of autonomous machinery in farming, providing results that demonstrate their (...) potential. (shrink)

This work provides proof-search algorithms and automated counter-model extraction for a class of STIT logics. With this, we answer an open problem concerning syntactic decision procedures and cut-free calculi for STIT logics. A new class of cut-free complete labelled sequent calculi G3LdmL^m_n, for multi-agent STIT with at most n-many choices, is introduced. We refine the calculi G3LdmL^m_n through the use of propagation rules and demonstrate the admissibility of their structural rules, resulting in auxiliary calculi Ldm^m_nL. In the single-agent case, we (...) show that the refined calculi Ldm^m_nL derive theorems within a restricted class of (forestlike) sequents, allowing us to provide proof-search algorithms that decide single-agent STIT logics. We prove that the proof-search algorithms are correct and terminate. (shrink)

Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on evidence about the (...) effectiveness of targeted advertising as well as empirical results about the nature of attentional control, I provide reasons to reject this argument. In turn, I use C. Thi Nguyen’s theory of value collapse to develop a new account of the harmfulness of automated influence. (shrink)

Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on evidence about the (...) effectiveness of targeted advertising as well as empirical results about the nature of attentional control, I provide reasons to reject this argument. In turn, I use C. Thi Nguyen's theory of value collapse to develop a new account of the harmfulness of automated influence. (shrink)

Agricultural innovation happens at different scales and through different streams. In the absence of a common global research agenda, decisions on which innovations are brought to existence, and through which methods, are taken with insufficient view on how innovation affects social relations, the environment, and future food production. Mostly, innovations are considered from the standpoint of economic efficiency, particularly in relationship to creating jobs for technology-exporting countries. Increasingly, however, the realization that innovations cannot be successful on their technical prowess (...) alone calls for a broader investigation. (shrink)

This project focuses on estimating reservoir inflows by integrating rainfall data, soil moisture levels in the catchment area, and releases from upstream reservoirs, coupled with an automated gate control system to prevent flooding in the basin. Utilizing hydrological models, the methodology predicts runoff from rainfall, adjusted for current soil moisture to enhance accuracy. Real-time data from upstream releases further refines inflow predictions. The automated system leverages predictive analytics and real-time monitoring to optimize gate operations, ensuring moderate water releases to maintain (...) safe reservoir levels and mitigate downstream flooding. This approach aims to enhance flood management and sustainable water resource use through advanced modelling and automation. (shrink)

This book offers a systematic and thorough philosophical analysis of the ways in which driving automation crosses path with ethical values. Upon introducing the different forms of driving automation and examining their relation to human autonomy, it provides readers with in-depth reflections on safety, privacy, moral judgment, control, responsibility, sustainability, and other ethical issues. Driving is undoubtedly a moral activity as a human act. Transferring it to artificial agents such as connected and automated vehicles necessarily raises many philosophical (...) questions. When driving is automated, what happens to its ethical dimensions? Could artificial agents accomplish ethical objectives on our behalf, take moral decisions in our place, and drive us into a more ethical transportation future? In doing so, would they be “moral” as we are or in a way that is similar to, but also remarkably different from, our own? And what role is yet to be played by human responsibility and commitment? The book addresses these questions with the aim of stimulating an interdisciplinary dialogue between different stakeholders. They include automotive engineers, computer scientists, and moral philosophers, as well as industry representatives, policymakers, regulators, transportation experts, and the general public. Indeed, connected and automated vehicles will not take the high road for us . We must drive them there. (shrink)

The article explores the problem of preferable technological changes in the context of work. To this end, it addresses the ‘why’ (motives and values) and the ‘how’ (organizational forms) of automation from a normative perspective. Concerning the ‘why,’ automation processes are currently mostly driven by values of economic efficiency. Yet, since automation processes are part of the basic structure of society, as is the division of labor, considerations of justice apply to them. As for the ‘how,’ the (...) article suggests ‘fair hybrid cooperation’ as an alternative ideal to guide automation priorities. It is achieved when the division of labor between humans and machines does not hinder, and preferably enables, workers’ experience of certain primary qualities in their work activity. By analogy with Rawls’ primary goods, these are qualities that it is necessary for every worker to experience in order to pursue their life plans: security, self-direction, self-development, dignity, and recognition. According to this criterion, the tasks to automate first are those hindering these contributive primary qualities. This provides us with a normative vocabulary and a standard to orient automation decisions but also to assess existing organizational forms and envisage alternative cooperative imaginaries. To illustrate how the ideal may play out in the real world, the article concludes with a ‘fair hybrid cooperation test’ and a nurse bots case for meaningful work. (shrink)

Automated influence, delivered by digital targeting technologies such as targeted advertising, digital nudges, and recommender systems, has attracted significant interest from both empirical researchers, on one hand, and critical scholars and policymakers on the other. In this paper, we argue for closer integration of these efforts. Critical scholars and policymakers, who focus primarily on the social, ethical, and political effects of these technologies, need empirical evidence to substantiate and motivate their concerns. However, existing empirical research investigating the effectiveness of these (...) technologies (or lack thereof), neglects other morally relevant effects—which can be felt regardless of whether or not the technologies "work" in the sense of fulfilling the promises of their designers. Drawing from the ethics and policy literature, we enumerate a range of questions begging for empirical analysis—the outline of a research agenda bridging these fields—and issue a call to action for more empirical research that takes these urgent ethics and policy questions as their starting point. (shrink)

Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means of automated (...) theorem provers and finite model builders. The fundamental theorem of Leibniz’s theory is derived using these tools. (shrink)

Agriculture in Bulgaria is one of sectors country’s economy in which significant changes have taken place over the past three decades: in the field of economic relations, the structure of farms, the size and production activity of enterprises, income and profit. These changes are due to the agrarian reform carried out in the 1990s, accession Bulgaria to the European Union, and the implementation of measures and mechanisms of the Common Agricultural Policy (CAP). In the period before accession Bulgaria to (...) the European Union (1997-2007) there were significant changes in the organization of agricultural sector of the economy, the formation of statistics, harmonization with European agricultural legislation, adaptation to dynamic changes in the environment. During the period of accession Bulgaria to the European Union, the conditions for functioning of agriculture relate to the formation of necessary mechanisms (organizational, financial, administrative, legal, informational, etc.) and successful adaptation to new realities. Bulgaria’s agriculture underwent significant changes during the COVID-19 pandemic, prompting the developing of appropriate financial support policies by the state and the European Union. For Bulgaria, agriculture is an important sector of the national economy for several reasons. First, it provides the population with food, on the quantitative and qualitative measurement of which depends the national food security of the country, raw materials for the food industry and resources for export. Secondly, favorable climatic conditions are suitable for growing various crops and farm animals. Third, agriculture accounts for 11.0% of gross domestic product, 12.5% of gross value added and employs 25.1% of the population. (shrink)

Human obsolescence is imminent. We are living through an era in which our activity is becoming less and less relevant to our well-being and to the fate of our planet. This trend toward increased obsolescence is likely to continue in the future, and we must do our best to prepare ourselves and our societies for this reality. Far from being a cause for despair, this is in fact an opportunity for optimism. Harnessed in the right way, the technology that hastens (...) our obsolescence can open us up to new utopian possibilities and enable heightened forms of human flourishing. (shrink)

While we are currently experiencing a renaissance in philosophical work on agriculture and food ( Barnhill, Budolfson, & Doggett 2016 ; Thompson 2015 ; Kaplan 2012 ), these topics were common sources of discussion throughout the three-thousand-year history of Western thought. For example, the Ancient Greek philosopher Aristotle (2014 ) explored connections between fulfi lling human promise and systems of agriculture ( Thompson & Noll 2015 ) and Hippocrates (1923 ) stressed the importance of cultivating agricultural products provided by (...) nature ( Zwart 2000 ). In order to live a truly human life, Hippocrates argued, one must not passively consume crude food products, as such brutish living leads to terrible suffering. Later, both the Hebrew Bible and Christian Gospels provided clear ethical mandates concerning agricultural practices and the consumption of food. These mandates or ethics needed to be observed regardless of context ( Zwart 2000 ). More recently, Thomas Jefferson added to this literature, as he engaged in agricultural production at his Monticello plantation and wrote extensively on how farming is intimately connected to the political system of democracy ( Thompson & Noll 2015 ). This refl ection on food and agriculture continued into the 20th century, albeit not in the discipline of philosophy. Scientists and agricultural leaders, such as Henry Wallace and Liberty Hyde Bailey, provided important critiques of agricultural practices contemporary to their time. (shrink)

Background: Food biofortification practices in agricultural sectors involve the process of employing biotechnology to enhance the nutritional content of crops during their growth process. Biofortification makes foods even more nutritious and highly functional for addressing malnutrition among children. These practices in farming industries need guidance and legal support from various national policies to support high-quality supplies of school meals fully. Aim: This study aims to analyze the association between various national policies and the implementation of food biofortification practices in (...) agricultural sectors among countries implementing school meal programs. Methods: The Bayesian Mindsponge Framework, combining the reasoning strengths of Mindsponge Theory and inference advantages of Bayesian analysis, was employed on a dataset of 126 government representatives who manage large-scale school meal programs in 126 different countries. Results: Findings showed that food safety policy was positively associated with food biofortification practices in agricultural sectors among countries implementing school meal programs. In contrast, nutrition policy had a significant negative association with these practices. Additionally, policies of school feeding, health, agriculture, and the private sector had unclear associations with food biofortification. Conclusions: Findings underscore the strong position of food safety policy in guiding food biofortification practices in agricultural sectors among countries implementing school meal programs. There is a need to re-assess the implemented nutrition policy due to its significant negative association with these practices. Enhancing and strengthening the policies of school feeding, health, agriculture, and the private sector may increase their potencies in giving positive impacts on food biofortification practices in agricultural sectors to ensure high-quality school meal supplies. (shrink)

Consumers are increasingly aware of the health- and safety-related implications of the food which they can buy in the market. At the same time, households have become more aware of their environmental responsibilities. Regarding the production of food, a crucial and multifunctional role is played by agriculture. The way vegetables, fruits, and other crops are grown and how livestock is raised has an impact on the environment and landscape. Operations performed by farmers, such as water management, can be dangerous for (...) the soil and the whole ecosystem. Consequently, there is a search for natural ways of sustaining the impact of agriculture on the environment. In this context, one of the most popular ideas is organic agriculture. In the literature on the subject, there are many concepts that some authors consider to be synonymous even as others argue that these terms are not interchangeable. There is, for example, "organic agriculture," "alternative agriculture," "sustainable agriculture," "ecological agriculture," "biological agriculture," "niche farming," "community-supported agriculture," and "integrated pest management." Very often, techniques and products related to organic agriculture are described by marketing experts with the use of abbreviations such as "bio" and "eco." Products with such markings and labels are increasingly popular in stores that often give them separate shelves for their sale. Despite the higher price compared to conventional products, they are increasingly sought by consumers. The entry examines the various impacts of organic agriculture with a view to these trends. (shrink)

Smart Farming Technologies raise ethical issues associated with the increased corporatization and industrialization of the agricultural sector. We explore the concept of biomimicry to conceptualize smart farming technologies as ecological innovations which are embedded in and in accordance with the natural environment. Such a biomimetic approach of smart farming technologies takes advantage of its potential to mitigate climate change, while at the same time avoiding the ethical issues related to the industrialization of the agricultural sector. We explore six (...) principles of a natural concept of biomimicry and apply these principles in the context of smart farming technologies. (shrink)

This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.

The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify cyberbullying (...) behavior in real-time, analyzing textual data from social media posts to detect harmful content. The model is trained on a large dataset of labeled instances of bullying and non-bullying content, using supervised ML algorithms such as Support Vector Machines (SVM), Decision Trees, and Random Forest. NLP techniques, including sentiment analysis, keyword extraction, and text vectorization, are employed to preprocess and transform the data into a format suitable for machine learning. To optimize the performance of the detection model, techniques such as Grid Search, Genetic Algorithms, and Particle Swarm Optimization are used to fine-tune hyperparameters, resulting in improved accuracy and reduced false positives. The system's effectiveness is validated through experiments conducted on various social media platforms, demonstrating its potential to detect cyberbullying with high precision. Future work will focus on enhancing the model's adaptability to emerging slang and evolving language patterns in social media. Key words: Cyberbullying Detection, Social Media, Supervised Machine Learning, Natural Language Processing (NLP), Optimization Techniques. (shrink)

Support for agricultural producers in the European Union remained uneven, as preferences were given to the most economically stable regions and businesses. Intensive farming methods continued to be used, with consequences for both the environment and animal health. In addition, the applicant countries that joined the European Union had to adopt legislation, i.e. meet the parameters and criteria that exist in the Single Market for agricultural products, namely: to ensure appropriate product quality, update the technical and technological base (...) of production, introduce innovative technologies for growing grain and fattening animals, etc. (shrink)

This book provides a critical reflection on automated science and addresses the question whether the computational tools we developed in last decades are changing the way we humans do science. More concretely: Can machines replace scientists in crucial aspects of scientific practice? The contributors to this book rethink and refine some of the main concepts by which science is understood, drawing a fascinating picture of the developments we expect over the next decades of human-machine co-evolution. The volume covers examples from (...) various fields and areas, such as molecular biology, climate modeling, clinical medicine, and artificial intelligence. The explosion of technological tools and drivers for scientific research calls for a renewed understanding of the human character of science. This book aims precisely to contribute to such a renewed understanding of science. (shrink)

We know that animals are harmed in plant production. Unfortunately, though, we know very little about the scale of the problem. This matters for two reasons. First, we can’t decide how many resources to devote to the problem without a better sense of its scope. Second, this information shortage throws a wrench in arguments for veganism, since it’s always possible that a diet that contains animal products is complicit in fewer deaths than a diet that avoids them. In this paper, (...) then, we have two aims: first, we want to collect and analyze all the available information about animal death associated with plant agriculture; second, we try to show just how difficult it’s to come up with a plausible estimate of how many animals are killed by plant agriculture, and not just because of a lack of empirical information. Additionally, we show that there are significant philosophical questions associated with interpreting the available data—questions such that different answers generate dramatically different estimates of the scope of the problem. Finally, we document current trends in plant agriculture that cause little or no collateral harm to animals, trends which suggest that field animal deaths are a historically contingent problem that in future may be reduced or eliminated altogether. (shrink)

This book reports on theoretical and practical analyses of the ethical challenges connected to driving automation. It also aims at discussing issues that have arisen from the European Commission 2020 report “Ethics of Connected and Automated Vehicles. Recommendations on Road Safety, Privacy, Fairness, Explainability and Responsibility”. Gathering contributions by philosophers, social scientists, mechanical engineers, and UI designers, the book discusses key ethical concerns relating to responsibility and personal autonomy, privacy, safety, and cybersecurity, as well as explainability and human-machine interaction. (...) On the one hand, it examines these issues from a theoretical, normative point of view. On the other hand, it proposes practical strategies to face the most urgent ethical problems, showing how the integration of ethics and technology can be achieved through design practices. All in all, this book fosters a multidisciplinary approach where philosophy, ethics, and engineering are integrated, rather than just juxtaposed. It is meant to inform and inspire an audience of philosophers of technology, ethicists, engineers, developers, manufacturers, and regulators, among other interested readers. (shrink)

A recent wave of academic and popular publications say that utopia is within reach: Automation will progress to such an extent and include so many high-skill tasks that much human work will soon become superfluous. The gains from this highly automated economy, authors suggest, could be used to fund a universal basic income (UBI). Today's employees would live off the robots' products and spend their days on intrinsically valuable pursuits. I argue that this prediction is unlikely to come true. (...) Historical precedent speaks against it, but the main problem is that the prediction fundamentally misunderstands how capitalism works—its incentives to increase or decrease production, its principles of income allocation, and the underlying conception of merit. (shrink)

Automated Influence is the use of Artificial Intelligence to collect, integrate, and analyse people’s data in order to deliver targeted interventions that shape their behaviour. We consider three central objections against Automated Influence, focusing on privacy, exploitation, and manipulation, showing in each case how a structural version of that objection has more purchase than its interactional counterpart. By rejecting the interactional focus of “AI Ethics” in favour of a more structural, political philosophy of AI, we show that the real problem (...) with Automated Influence is the crisis of legitimacy that it precipitates. (shrink)

This article will rework the classical question ‘Can a machine think?’ into a more specific problem: ‘Can a machine think anything new?’ It will consider traditional computational tasks such as prediction and decision-making, so as to investigate whether the instrumentality of these operations can be understood in terms of the creation of novel thought. By addressing philosophical and technoscientific attempts to mechanise thought on the one hand, and the philosophical and cultural critique of these attempts on the other, I will (...) argue that computation’s epistemic productions should be assessed vis-à-vis the logico-mathematical specificity of formal axiomatic systems. Such an assessment requires us to conceive automated modes of thought in such a way as to supersede the hope that machines might replicate human cognitive faculties, and to thereby acknowledge a form of onto-epistemological autonomy in automated ‘thinking’ processes. This involves moving beyond the view that machines might merely simulate humans. Machine thought should be seen as dramatically alien to human thought, and to the dimension of lived experience upon which the latter is predicated. Having stepped outside the simulative paradigm, the question ‘Can a machine think anything new?’ can then be reformulated. One should ask whether novel behaviour in computing might come not from the breaking of mechanical rules, but from following them: from doing what computers do already, and not what we might think they should be doing if we wanted them to imitate us. (shrink)

Technology has the power to break the limitations of traditional passive learning and innovate almost all aspects of everyday life with the power of connecting things of the world to the Internet, “Internet of Things (IoT).” IoT is no longer a phenomenon, but it has become a prevalent system in which people, processes, data, and things connect to the Internet and each other. This paper ‘Enhanced Campus Automation System and the emerging need of IoT integration: an automation perspective’ (...) [eCAS-IoT] is an outcome of case study undertaken at St. Aloysius’ College, Jabalpur, India, wherein the automation challenges are taken into consideration that has been integrated in the existing ERP and related tools such as RFID based attendance and monitoring system in real-time, digital library, API integration and implementation of Optical Network. In this paper we have tried to bring out ideas to achieve the campus automation challenges and awareness of greater need of technical expertise, promotion and training on the effective use of ICT and related devices to make teaching, learning and administration more impacting. (shrink)

Many of the benefits and burdens we might experience in our lives — from bank loans to bail terms — are increasingly decided by institutions relying on algorithms. In a sense, this is nothing new: algorithms — instructions whose steps can, in principle, be mechanically executed to solve a decision problem — are at least as old as allocative social institutions themselves. Algorithms, after all, help decision-makers to navigate the complexity and variation of whatever domains they are designed for. In (...) another sense, however, this development is startlingly new: not only are algorithms being deployed in ever more social contexts, they are being mechanically executed not merely in principle, but pervasively in practice. Due to recent advances in computing technology, the benefits and burdens we experience in our lives are now increasingly decided by automata, rather than each other. How are we to morally assess these technologies? In this chapter, I propose a preliminary conceptual schema for identifying and locating the various injustices of automated, algorithmic social decision systems, from a broadly liberal perspective. (shrink)

Standpoint logic is a recently proposed formalism in the context of knowledge integration, which advocates a multi-perspective approach permitting reasoning with a selection of diverse and possibly conflicting standpoints rather than forcing their unification. In this paper, we introduce nested sequent calculi for propositional standpoint logics---proof systems that manipulate trees whose nodes are multisets of formulae---and show how to automate standpoint reasoning by means of non-deterministic proof-search algorithms. To obtain worst-case complexity-optimal proof-search, we introduce a novel technique in the context (...) of nested sequents, referred to as "coloring," which consists of taking a formula as input, guessing a certain coloring of its subformulae, and then running proof-search in a nested sequent calculus on the colored input. Our technique lets us decide the validity of standpoint formulae in CoNP since proof-search only produces a partial proof relative to each permitted coloring of the input. We show how all partial proofs can be fused together to construct a complete proof when the input is valid, and how certain partial proofs can be transformed into a counter-model when the input is invalid. These "certificates" (i.e. proofs and counter-models) serve as explanations of the (in)validity of the input. (shrink)

Artificial intelligence (AI) technologies are used in various domains of human activities, and one of these domains is scientific research. Now, researchers in many scientific areas try to apply AI technologies to their research and automate it. These researchers claim that the ‘automation of science’ will liberate people from non-creative tasks in scientific research, and radically change the overall state of science and technology so that large-scale innovation results. As I see it, the automation of science is remarkable (...) in another respect: since science is one of the most distinctive human activities, the tendency of automating it prompts us to reconsider the aspects of our humanity itself. One of these aspects is concerned with human creativity, on which this article focuses. In this article, I address two questions concerning the automation of science: first, ‘Can AI makes creative discovery?’; second, ‘What implications may the automation of science have on science and society?’. Scientific discovery is said to be one of the most creative phases of scientific research. I show that, though there are no reasons in principle why AI could not make creative discovery, we do not at present have enough knowledge how to realize it. If the automation of science nevertheless proceeds, the cultural values science as a creative activity has might be reduced, and it might alter the state of scientific community and its relationship with society in some undesirable way. Therefore, I conclude, we need to specify desirable ways of introducing AI technologies into science and devise measures against demerits of automating science. (shrink)

In this paper I critique the ethical implications of automating CCTV surveillance. I consider three modes of CCTV with respect to automation: manual, fully automated, and partially automated. In each of these I examine concerns posed by processing capacity, prejudice towards and profiling of surveilled subjects, and false positives and false negatives. While it might seem as if fully automated surveillance is an improvement over the manual alternative in these areas, I demonstrate that this is not necessarily the case. (...) In preference to the extremes I argue in favour of partial automation in which the system integrates a human CCTV operator with some level of automation. To assess the degree to which such a system should be automated I draw on the further issues of privacy and distance. Here I argue that the privacy of the surveilled subject can benefit from automation, while the distance between the surveilled subject and the CCTV operator introduced by automation can have both positive and negative effects. I conclude that in at least the majority of cases more automation is preferable to less within a partially automated system where this does not impinge on efficacy. (shrink)

We are already past the point where climate change mitigation alone does not suffice and major efforts need to be undertaken to adapt agriculture to climate change. As this situation was both foreseeable and avoidable, it is urgent to see that particularly people who have historically contributed the least to climate change do not end up assuming most of the costs. Climate change will have the worst effects on agriculture in the tropical region in the form of droughts, extreme heat (...) waves and massive storms. The historical unequal contributions to climate change and its unjustly distributed consequences morally oblige us to distribute global adaptation costs fairly. Yet to have a full understanding of the social implications of adapting to climate change we need to look beyond making adaptation technologies accessible and available. Using a social justice framework, I defend fair prices of adaptation technologies as a demand of justice in exchange, an allocation of research attention proportional to urgent global needs as distributive justice, inclusive technology development and governance as contributive justice and addressing the interests of future generations as intergenerational justice. (shrink)

As automating technologies are increasingly integrated into workplaces, one concern is that many of the human workers who remain will be relegated to more dull and less positively impactful work. This paper considers two rival theories of meaningful work that might be used to evaluate particular implementations of automation. The first is achievementism, which says that work that culminates in achievements to workers’ credit is especially meaningful; the other is the practice view, which says that work that takes the (...) form of an open-ended practice is especially meaningful. Of the two, the practice view is the better tool for assessing the future of meaningful work, because achievementism is explanatorily inadequate in two ways. Moreover, the practice view can explain why the most meaningful forms of work cannot be automated. A procedure can only be automated as long as the steps are defined, whereas, in such work, which steps to take is indefinitely open to redefinition. This reveals the real threat to meaningful work to be a political-economic one. The relevant ethical questions there have to do with how much creative control workers retain in crafting their own jobs, when those jobs involve meaningful work in collaboration with machines; and how to liberate workers from jobs that do not involve meaningful work, which should be left to machines anyway. (shrink)

REVIEW OF: Automated Development of Fundamental Mathematical Theories by Art Quaife. (1992: Kluwer Academic Publishers) 271pp. Using the theorem prover OTTER Art Quaife has proved four hundred theorems of von Neumann-Bernays-Gödel set theory; twelve hundred theorems and definitions of elementary number theory; dozens of Euclidean geometry theorems; and Gödel's incompleteness theorems. It is an impressive achievement. To gauge its significance and to see what prospects it offers this review looks closely at the book and the proofs it presents.

Important decisions that impact humans lives, livelihoods, and the natural environment are increasingly being automated. Delegating tasks to so-called automated decision-making systems can improve efficiency and enable new solutions. However, these benefits are coupled with ethical challenges. For example, ADMS may produce discriminatory outcomes, violate individual privacy, and undermine human self-determination. New governance mechanisms are thus needed that help organisations design and deploy ADMS in ways that are ethical, while enabling society to reap the full economic and social benefits of (...) automation. In this article, we consider the feasibility and efficacy of ethics-based auditing as a governance mechanism that allows organisations to validate claims made about their ADMS. Building on previous work, we define EBA as a structured process whereby an entity’s present or past behaviour is assessed for consistency with relevant principles or norms. We then offer three contributions to the existing literature. First, we provide a theoretical explanation of how EBA can contribute to good governance by promoting procedural regularity and transparency. Second, we propose seven criteria for how to design and implement EBA procedures successfully. Third, we identify and discuss the conceptual, technical, social, economic, organisational, and institutional constraints associated with EBA. We conclude that EBA should be considered an integral component of multifaced approaches to managing the ethical risks posed by ADMS. (shrink)

Advances in AI are powering increasingly precise and widespread computational propaganda, posing serious threats to national security. The military and intelligence communities are starting to discuss ways to engage in this space, but the path forward is still unclear. These developments raise pressing ethical questions, about which existing ethics frameworks are silent. Understanding these challenges through the lens of “cognitive security,” we argue, offers a promising approach.

This thesis examines the prospects for mechanical procedures that can identify true, complete, universal, first-order logical theories on the basis of a complete enumeration of true atomic sentences. A sense of identification is defined that is more general than those which are usually studied in the learning theoretic and inductive inference literature. Some identification algorithms based on confirmation relations familiar in the philosophy of science are presented. Each of these algorithms is shown to identify all purely universal theories without function (...) symbols. It is demonstrated that no procedure can solve this universal theory inference problem in the more usual senses of identification. The question of efficiency for theory inference systems is addressed, and some definitions of limiting complexity are examined. It is shown that several aspects of obvious strategies for solving the universal theory inference problem are NP-hard. Finally, some non-worst case heuristic search strategies are examined in light of these NP-completeness results. These strategies are based upon an isomorphism between clausal entailments of a certain class and partition lattices, and are applicable to the improvement of earlier work on language acquisition and logical inductive inference. (shrink)

One recent priority of the U.S. government is developing autonomous robotic systems. The U.S. Army has funded research to design a metric of evil to support military commanders with ethical decision-making and, in the future, allow robotic military systems to make autonomous ethical judgments. We use this particular project as a case study for efforts that seek to frame morality in quantitative terms. We report preliminary results from this research, describing the assumptions and limitations of a program that assesses the (...) relative evil of two courses of action. We compare this program to other attempts to simulate ethical decision-making, assess possibilities for overcoming the trade-off between input simplification and output reliability, and discuss the responsibilities of users and designers in implementing such programs. We conclude by discussing the implications that this project highlights for the successes and challenges of developing automated mechanisms for ethical decision making. (shrink)